Data visualization

Brainstorming

  • Why do we visualize data?
  • What elements does a good graph contain?
  • How are these elements called?

Boxplots from Carlson 2017

Basic ggplot() syntax

ggplot(data = <your data frame>, mapping = aes(x = <variable to be mapped to axis x>)) + 
   geom_<geometry>()
  1. Function ggplot() takes the data frame as an argument.
  2. argument aes() serves to map aesthetics (axis x and y, colors etc.) to different variables from your data frame.
  3. Functions with geom_ prefix are geometries, ie. types of plots to draw. You can set specific arguments such as the color or shape here.
  4. Note the + after each layer of the ggplot

Geoms for one variable:

  • geom_histogram()
  • geom_density()
  • geom_bar()

Plots for one variable

Histogram

  • Distribution of values of a quantitative variable.

Distribution of dart point weights.

ggplot(data = df_dartpoints, mapping =  aes(x = Length)) +
   geom_histogram()

Histogram

  • note that you don’t need to write arguments data = and mapping =
ggplot(df_dartpoints, aes(x = Length)) +
  geom_histogram(binwidth = 5)

Histogram

ggplot(df_dartpoints, aes(x = Length))+
  geom_histogram(binwidth = 5, color = "black")

Histogram

ggplot(df_dartpoints, aes(x = Length)) +
  geom_histogram(binwidth = 5, color = "black", fill = "white")

Labels

ggplot(df_dartpoints, aes(x = Length)) +
  geom_histogram(binwidth = 5, color = "black", fill = "white") +
  labs(x = "Length (cm)", y = "Count")

Labels

ggplot(df_dartpoints, aes(x = Length)) +
  geom_histogram(binwidth = 5, color = "black", fill = "white") +
  labs(x = "Length (cm)", y = "Count",
       title = "Histogram of dart point lengths")

Labels

ggplot(df_dartpoints, aes(x = Length))+
  geom_histogram(binwidth = 5, color = "black", fill = "white") +
  labs(x = "Length (cm)", y = "Count",
       title = "Histogram of dart point lengths", 
       caption = "Data adapted from archdata R package, Carlson 2017")

Density plot

  • Distribution of values of a quantitative variable.

Distribution of dart point weights.

ggplot(df_dartpoints, aes(x = Length)) +
  geom_density()

Density plot - setting the color

ggplot(df_dartpoints, aes(x = Length)) +
  geom_density(color = "red")

Density plot - mapping variables by color

ggplot(df_dartpoints, aes(x = Length, color = Name)) +
  geom_density()

Density plot

ggplot(df_dartpoints, aes(x = Length, color = Name, fill = Name)) +
  geom_density()

Density plot

ggplot(df_dartpoints, aes(x = Length, color = Name, fill = Name)) + 
  geom_density(alpha = 0.4)

Bar chart

  • Distribution of values of a qualitative variable.

Distribution of types of dart points.

ggplot(data = df_dartpoints, aes(x = Name)) + 
  geom_bar()

Bar chart

ggplot(data = df_dartpoints, aes(x = Name, color = Name)) + 
  geom_bar()

Bar chart

ggplot(data = df_dartpoints, aes(x = Name, color = Name, fill = Name)) +
  geom_bar()

Bar chart

  • notice here the difference between setting color of our choice and mapping color based on one variable
ggplot(data = df_dartpoints, aes(x = Name, fill = Name)) + 
  geom_bar(color = "black")